Understanding Spivak's Proof of Unique Derivative: A Holiday Challenge

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SUMMARY

The discussion focuses on Spivak's proof of the unique derivative as presented in "Calculus on Manifolds." The key points addressed include the application of the triangle inequality to establish the ≤ inequality and the demonstration of linearity for the constants λ and μ. The proof involves manipulating expressions to show that the ratio of differences converges appropriately, confirming the validity of the last equality in the proof. These insights clarify the foundational concepts necessary for understanding the proof's structure.

PREREQUISITES
  • Understanding of calculus concepts, specifically derivatives.
  • Familiarity with Spivak's "Calculus on Manifolds."
  • Knowledge of linearity in mathematical functions.
  • Basic grasp of inequalities, particularly the triangle inequality.
NEXT STEPS
  • Study the triangle inequality in depth and its applications in calculus.
  • Review the concept of linearity in mathematical functions and its implications.
  • Examine Spivak's proofs in "Calculus on Manifolds" for further context.
  • Explore advanced topics in differential calculus related to unique derivatives.
USEFUL FOR

Students of advanced calculus, mathematicians interested in proof techniques, and anyone studying Spivak's "Calculus on Manifolds" who seeks a deeper understanding of unique derivatives.

mathlove1
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Hi--

I am trying to work through Spivak's Calculus on Manifolds over the holidays, and I am a little stuck on his proof of the unique derivative (on p. 16 as well as below).

Specifically,
(i) Why does the ≤ inequality hold, and
(ii) Why does the last equality of the second-to-last-line hold?

I would very much appreciate any help!
 

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(i) The triangle inequality [tex]|x+y|\leq |x|+|y|[/tex]

(ii) Linearity of [itex]\lambda[/itex] and [itex]\mu[/itex]:

[tex]\frac{|\lambda(tx)-\mu(tx)|}{|tx|} = \frac{|t\lambda(x)-t\mu(x)|}{|tx|} = \frac{|t||\lambda(x)-\mu(x)|}{|t||x|} = \frac{|\lambda(x)-\mu(x)|}{|x|}[/tex]
 
Thanks so much!
 

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